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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 hours ago
centre for research in artificial intelligence and machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern thinking, connecting decades
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the recruitment process. To Be Successful You Will Need A PhD qualification in a relevant discipline, e.g. aerospace/computer/electrical/mechanical or mechatronic engineering Knowledge of machine learning, image
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Australian National University | Canberra, Australian Capital Territory | Australia | about 22 hours ago
Integrated Planning & Learning and Reinforcement Learning in non-deterministic and partially-observed scenarios. The methods will be evaluated on physical robots. The ideal candidate would have: A PhD (or
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and immunotherapy research, a well-established clinical trial network, and recognised leadership in producing industry-ready graduates. With strong expertise and experience in AI and machine learning
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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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training materials for research teams, focusing on data science and machine learning techniques in geoscience. Position description: PD [Research Fellow] [520112].pdf To learn more about this opportunity
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of Form Level A or B appointment - $88,290 - $145,730 (min. 110,059 with PhD) + 17% superannuation Full-time, fixed term contracts to May 2027 Why Your Role Matters: The Defence Trailblazer for Concept
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for uncertainty quantification in learned computer vision. The person should have a PhD in Computer Vision or a closely related field, and a demonstrated strong track record in this field. This should include
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area of expertise. You may be a great fit if: You are a passionate researcher with a PhD in Computer Science or a related field, experienced in machine learning for spatial data management, with a track
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and standing recognised by the University/profession as appropriate for the relevant discipline area (e.g., AI/Machine Learning, Bioinformatics). A proven track record of research and scholarly